Data Science Team Intern

Job description

The Data Science Team is SCOR’s center of expertise on advanced analytics topics (including Machine Learning, Natural Language Processing) in both P&C and L&H business, as part of the Knowledge division. It has the responsibility to enhance SCOR’s data capabilities in order to help innovate processes such as underwriting or claims by creatively applying cutting edge Data Science techniques. Data Scientists are also involved in delivering solutions (survival analysis, interpretability, …) and spreading Data Science knowledge within the division.

SCOR is working to bridge the protection gap, widening the limits as far as possible by offering new products and improved services. Meanwhile, the horizon of emerging risks is expanding, with a particular need to better understand the threat of climate change. Building resilience in this rapidly evolving landscape is our challenge, as well as our opportunity.

The position is based in Paris and it will have a duration up to 6 months. It can be either an Actuarial internship or a Data Science one. As the Data Science Team’s projects portfolio is regularly updated, the internship project will be discussed with the candidates during the interviews. The internship project themes will potentially involve survival modelling, model de-biasing, information extraction from documents, image analysis, …

·  Good programming skills & knowledge of common data science languages such as Python. 
·  Good knowledge of supervised/unsupervised machine learning techniques, Deep Learning with application to NLP or Computer Vision is a plus.
·  Good writing capabilities
·  Fluency in English (International context and relationships with various entities of SCOR)
·  Insurance industry experience is preferred, but not mandatory
·  Prepare a report on state-of-the-art solutions and ideas concerning the chosen topic.
·  Share knowledge on advanced topics with the team (incl. the Knowledge division).
·  Develop a proof-of-concept solution of the chosen problem.
·  Participate in the industrialization of the proof of concept and familiarize with development skills (such as git, Python, code documentation, unit testing).
·  If desired and depending on the project, interact with internal non-technical stakeholders.